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    "# Generative Adversarial Networks (GANs)\n",
    "\n",
    "So far in CS231N, all the applications of neural networks that we have explored have been **discriminative models** that take an input and are trained to produce a labeled output. This has ranged from straightforward classification of image categories to sentence generation (which was still phrased as a classification problem, our labels were in vocabulary space and we’d learned a recurrence to capture multi-word labels). In this notebook, we will expand our repetoire, and build **generative models** using neural networks. Specifically, we will learn how to build models which generate novel images that resemble a set of training images.\n",
    "\n",
    "### What is a GAN?\n",
    "\n",
    "In 2014, [Goodfellow et al.](https://arxiv.org/abs/1406.2661) presented a method for training generative models called Generative Adversarial Networks (GANs for short). In a GAN, we build two different neural networks. Our first network is a traditional classification network, called the **discriminator**. We will train the discriminator to take images, and classify them as being real (belonging to the training set) or fake (not present in the training set). Our other network, called the **generator**, will take random noise as input and transform it using a neural network to produce images. The goal of the generator is to fool the discriminator into thinking the images it produced are real.\n",
    "\n",
    "We can think of this back and forth process of the generator ($G$) trying to fool the discriminator ($D$), and the discriminator trying to correctly classify real vs. fake as a minimax game:\n",
    "$$\\underset{G}{\\text{minimize}}\\; \\underset{D}{\\text{maximize}}\\; \\mathbb{E}_{x \\sim p_\\text{data}}\\left[\\log D(x)\\right] + \\mathbb{E}_{z \\sim p(z)}\\left[\\log \\left(1-D(G(z))\\right)\\right]$$\n",
    "where $z \\sim p(z)$ are the random noise samples, $G(z)$ are the generated images using the neural network generator $G$, and $D$ is the output of the discriminator, specifying the probability of an input being real. In [Goodfellow et al.](https://arxiv.org/abs/1406.2661), they analyze this minimax game and show how it relates to minimizing the Jensen-Shannon divergence between the training data distribution and the generated samples from $G$.\n",
    "\n",
    "To optimize this minimax game, we will aternate between taking gradient *descent* steps on the objective for $G$, and gradient *ascent* steps on the objective for $D$:\n",
    "1. update the **generator** ($G$) to minimize the probability of the __discriminator making the correct choice__. \n",
    "2. update the **discriminator** ($D$) to maximize the probability of the __discriminator making the correct choice__.\n",
    "\n",
    "While these updates are useful for analysis, they do not perform well in practice. Instead, we will use a different objective when we update the generator: maximize the probability of the **discriminator making the incorrect choice**. This small change helps to allevaiate problems with the generator gradient vanishing when the discriminator is confident. This is the standard update used in most GAN papers, and was used in the original paper from [Goodfellow et al.](https://arxiv.org/abs/1406.2661). \n",
    "\n",
    "In this assignment, we will alternate the following updates:\n",
    "1. Update the generator ($G$) to maximize the probability of the discriminator making the incorrect choice on generated data:\n",
    "$$\\underset{G}{\\text{maximize}}\\;  \\mathbb{E}_{z \\sim p(z)}\\left[\\log D(G(z))\\right]$$\n",
    "2. Update the discriminator ($D$), to maximize the probability of the discriminator making the correct choice on real and generated data:\n",
    "$$\\underset{D}{\\text{maximize}}\\; \\mathbb{E}_{x \\sim p_\\text{data}}\\left[\\log D(x)\\right] + \\mathbb{E}_{z \\sim p(z)}\\left[\\log \\left(1-D(G(z))\\right)\\right]$$\n",
    "\n",
    "### What else is there?\n",
    "Since 2014, GANs have exploded into a huge research area, with massive [workshops](https://sites.google.com/site/nips2016adversarial/), and [hundreds of new papers](https://github.com/hindupuravinash/the-gan-zoo). Compared to other approaches for generative models, they often produce the highest quality samples but are some of the most difficult and finicky models to train (see [this github repo](https://github.com/soumith/ganhacks) that contains a set of 17 hacks that are useful for getting models working). Improving the stabiilty and robustness of GAN training is an open research question, with new papers coming out every day! For a more recent tutorial on GANs, see [here](https://arxiv.org/abs/1701.00160). There is also some even more recent exciting work that changes the objective function to Wasserstein distance and yields much more stable results across model architectures: [WGAN](https://arxiv.org/abs/1701.07875), [WGAN-GP](https://arxiv.org/abs/1704.00028).\n",
    "\n",
    "\n",
    "GANs are not the only way to train a generative model! For other approaches to generative modeling check out the [deep generative model chapter](http://www.deeplearningbook.org/contents/generative_models.html) of the Deep Learning [book](http://www.deeplearningbook.org). Another popular way of training neural networks as generative models is Variational Autoencoders (co-discovered [here](https://arxiv.org/abs/1312.6114) and [here](https://arxiv.org/abs/1401.4082)). Variatonal autoencoders combine neural networks with variationl inference to train deep generative models. These models tend to be far more stable and easier to train but currently don't produce samples that are as pretty as GANs.\n",
    "\n",
    "Here's an example of what your outputs from the 3 different models you're going to train should look like... note that GANs are sometimes finicky, so your outputs might not look exactly like this... this is just meant to be a *rough* guideline of the kind of quality you can expect:\n",
    "\n",
    "![caption](gan_outputs_pytorch.png)"
   ]
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   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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    ]
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   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "from torch.nn import init\n",
    "import torchvision\n",
    "import torchvision.transforms as T\n",
    "import torch.optim as optim\n",
    "from torch.utils.data import DataLoader\n",
    "from torch.utils.data import sampler\n",
    "import torchvision.datasets as dset\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "def show_images(images):\n",
    "    images = np.reshape(images, [images.shape[0], -1])  # images reshape to (batch_size, D)\n",
    "    sqrtn = int(np.ceil(np.sqrt(images.shape[0])))\n",
    "    sqrtimg = int(np.ceil(np.sqrt(images.shape[1])))\n",
    "\n",
    "    fig = plt.figure(figsize=(sqrtn, sqrtn))\n",
    "    gs = gridspec.GridSpec(sqrtn, sqrtn)\n",
    "    gs.update(wspace=0.05, hspace=0.05)\n",
    "\n",
    "    for i, img in enumerate(images):\n",
    "        ax = plt.subplot(gs[i])\n",
    "        plt.axis('off')\n",
    "        ax.set_xticklabels([])\n",
    "        ax.set_yticklabels([])\n",
    "        ax.set_aspect('equal')\n",
    "        plt.imshow(img.reshape([sqrtimg,sqrtimg]))\n",
    "    return \n",
    "\n",
    "def preprocess_img(x):\n",
    "    return 2 * x - 1.0\n",
    "\n",
    "def deprocess_img(x):\n",
    "    return (x + 1.0) / 2.0\n",
    "\n",
    "def rel_error(x,y):\n",
    "    return np.max(np.abs(x - y) / (np.maximum(1e-8, np.abs(x) + np.abs(y))))\n",
    "\n",
    "def count_params(model):\n",
    "    \"\"\"Count the number of parameters in the current TensorFlow graph \"\"\"\n",
    "    param_count = np.sum([np.prod(p.size()) for p in model.parameters()])\n",
    "    return param_count\n",
    "\n",
    "answers = dict(np.load('gan-checks-tf.npz'))"
   ]
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   "source": [
    "## Dataset\n",
    " GANs are notoriously finicky with hyperparameters, and also require many training epochs. In order to make this assignment approachable without a GPU, we will be working on the MNIST dataset, which is 60,000 training and 10,000 test images. Each picture contains a centered image of white digit on black background (0 through 9). This was one of the first datasets used to train convolutional neural networks and it is fairly easy -- a standard CNN model can easily exceed 99% accuracy. \n",
    "\n",
    "To simplify our code here, we will use the PyTorch MNIST wrapper, which downloads and loads the MNIST dataset. See the [documentation](https://github.com/pytorch/vision/blob/master/torchvision/datasets/mnist.py) for more information about the interface. The default parameters will take 5,000 of the training examples and place them into a validation dataset. The data will be saved into a folder called `MNIST_data`. "
   ]
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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false,
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   "outputs": [
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\n",
      "text/plain": [
       "<Figure size 864x864 with 128 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "class ChunkSampler(sampler.Sampler):\n",
    "    \"\"\"Samples elements sequentially from some offset. \n",
    "    Arguments:\n",
    "        num_samples: # of desired datapoints\n",
    "        start: offset where we should start selecting from\n",
    "    \"\"\"\n",
    "    def __init__(self, num_samples, start=0):\n",
    "        self.num_samples = num_samples\n",
    "        self.start = start\n",
    "\n",
    "    def __iter__(self):\n",
    "        return iter(range(self.start, self.start + self.num_samples))\n",
    "\n",
    "    def __len__(self):\n",
    "        return self.num_samples\n",
    "\n",
    "NUM_TRAIN = 50000\n",
    "NUM_VAL = 5000\n",
    "\n",
    "NOISE_DIM = 96\n",
    "batch_size = 128\n",
    "\n",
    "mnist_train = dset.MNIST('./cs231n/datasets/MNIST_data', train=True, download=True,\n",
    "                           transform=T.ToTensor())\n",
    "loader_train = DataLoader(mnist_train, batch_size=batch_size,\n",
    "                          sampler=ChunkSampler(NUM_TRAIN, 0))\n",
    "\n",
    "mnist_val = dset.MNIST('./cs231n/datasets/MNIST_data', train=True, download=True,\n",
    "                           transform=T.ToTensor())\n",
    "loader_val = DataLoader(mnist_val, batch_size=batch_size,\n",
    "                        sampler=ChunkSampler(NUM_VAL, NUM_TRAIN))\n",
    "\n",
    "\n",
    "imgs = loader_train.__iter__().next()[0].view(batch_size, 784).numpy().squeeze()\n",
    "show_images(imgs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Noise\n",
    "Generate uniform noise from -1 to 1 with shape `[batch_size, dim]`.\n",
    "\n",
    "Hint: use `torch.rand`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sample_noise(batch_size, dim):\n",
    "    \"\"\"\n",
    "    Generate a PyTorch Tensor of uniform random noise.\n",
    "\n",
    "    Input:\n",
    "    - batch_size: Integer giving the batch size of noise to generate.\n",
    "    - dim: Integer giving the dimension of noise to generate.\n",
    "    \n",
    "    Output:\n",
    "    - A PyTorch Tensor of shape (batch_size, dim) containing uniform\n",
    "      random noise in the range (-1, 1).\n",
    "    \"\"\"\n",
    "    # *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "    return torch.rand(batch_size, dim)*2 - 1.\n",
    "\n",
    "    # *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make sure noise is the correct shape and type:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All tests passed!\n"
     ]
    }
   ],
   "source": [
    "def test_sample_noise():\n",
    "    batch_size = 3\n",
    "    dim = 4\n",
    "    torch.manual_seed(231)\n",
    "    z = sample_noise(batch_size, dim)\n",
    "    np_z = z.cpu().numpy()\n",
    "    assert np_z.shape == (batch_size, dim)\n",
    "    assert torch.is_tensor(z)\n",
    "    assert np.all(np_z >= -1.0) and np.all(np_z <= 1.0)\n",
    "    assert np.any(np_z < 0.0) and np.any(np_z > 0.0)\n",
    "    print('All tests passed!')\n",
    "    \n",
    "test_sample_noise()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "source": [
    "## Flatten\n",
    "\n",
    "Recall our Flatten operation from previous notebooks... this time we also provide an Unflatten, which you might want to use when implementing the convolutional generator. We also provide a weight initializer (and call it for you) that uses Xavier initialization instead of PyTorch's uniform default."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [],
   "source": [
    "class Flatten(nn.Module):\n",
    "    def forward(self, x):\n",
    "        N, C, H, W = x.size() # read in N, C, H, W\n",
    "        return x.view(N, -1)  # \"flatten\" the C * H * W values into a single vector per image\n",
    "    \n",
    "class Unflatten(nn.Module):\n",
    "    \"\"\"\n",
    "    An Unflatten module receives an input of shape (N, C*H*W) and reshapes it\n",
    "    to produce an output of shape (N, C, H, W).\n",
    "    \"\"\"\n",
    "    def __init__(self, N=-1, C=128, H=7, W=7):\n",
    "        super(Unflatten, self).__init__()\n",
    "        self.N = N\n",
    "        self.C = C\n",
    "        self.H = H\n",
    "        self.W = W\n",
    "    def forward(self, x):\n",
    "        return x.view(self.N, self.C, self.H, self.W)\n",
    "\n",
    "def initialize_weights(m):\n",
    "    if isinstance(m, nn.Linear) or isinstance(m, nn.ConvTranspose2d):\n",
    "        init.xavier_uniform_(m.weight.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "source": [
    "## CPU / GPU\n",
    "By default all code will run on CPU. GPUs are not needed for this assignment, but will help you to train your models faster. If you do want to run the code on a GPU, then change the `dtype` variable in the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [],
   "source": [
    "#dtype = torch.FloatTensor\n",
    "dtype = torch.cuda.FloatTensor ## UNCOMMENT THIS LINE IF YOU'RE ON A GPU!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Discriminator\n",
    "Our first step is to build a discriminator. Fill in the architecture as part of the `nn.Sequential` constructor in the function below. All fully connected layers should include bias terms. The architecture is:\n",
    " * Fully connected layer with input size 784 and output size 256\n",
    " * LeakyReLU with alpha 0.01\n",
    " * Fully connected layer with input_size 256 and output size 256\n",
    " * LeakyReLU with alpha 0.01\n",
    " * Fully connected layer with input size 256 and output size 1\n",
    " \n",
    "Recall that the Leaky ReLU nonlinearity computes $f(x) = \\max(\\alpha x, x)$ for some fixed constant $\\alpha$; for the LeakyReLU nonlinearities in the architecture above we set $\\alpha=0.01$.\n",
    " \n",
    "The output of the discriminator should have shape `[batch_size, 1]`, and contain real numbers corresponding to the scores that each of the `batch_size` inputs is a real image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def discriminator():\n",
    "    \"\"\"\n",
    "    Build and return a PyTorch model implementing the architecture above.\n",
    "    \"\"\"\n",
    "    model = nn.Sequential(\n",
    "            # *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "            Flatten(),\n",
    "            nn.Linear(784, 256),\n",
    "            nn.LeakyReLU(0.01),\n",
    "            nn.Linear(256, 256),\n",
    "            nn.LeakyReLU(0.01),\n",
    "            nn.Linear(256, 1),\n",
    "\n",
    "            # *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "    )\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test to make sure the number of parameters in the discriminator is correct:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct number of parameters in discriminator.\n"
     ]
    }
   ],
   "source": [
    "def test_discriminator(true_count=267009):\n",
    "    model = discriminator()\n",
    "    cur_count = count_params(model)\n",
    "    if cur_count != true_count:\n",
    "        print('Incorrect number of parameters in discriminator. Check your achitecture.')\n",
    "    else:\n",
    "        print('Correct number of parameters in discriminator.')     \n",
    "\n",
    "test_discriminator()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generator\n",
    "Now to build the generator network:\n",
    " * Fully connected layer from noise_dim to 1024\n",
    " * `ReLU`\n",
    " * Fully connected layer with size 1024 \n",
    " * `ReLU`\n",
    " * Fully connected layer with size 784\n",
    " * `TanH` (to clip the image to be in the range of [-1,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generator(noise_dim=NOISE_DIM):\n",
    "    \"\"\"\n",
    "    Build and return a PyTorch model implementing the architecture above.\n",
    "    \"\"\"\n",
    "    model = nn.Sequential(\n",
    "            # *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "            nn.Linear(noise_dim, 1024),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(1024, 1024),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(1024, 784),\n",
    "            nn.Tanh(),\n",
    "\n",
    "            # *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "    )\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test to make sure the number of parameters in the generator is correct:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct number of parameters in generator.\n"
     ]
    }
   ],
   "source": [
    "def test_generator(true_count=1858320):\n",
    "    model = generator(4)\n",
    "    cur_count = count_params(model)\n",
    "    if cur_count != true_count:\n",
    "        print('Incorrect number of parameters in generator. Check your achitecture.')\n",
    "    else:\n",
    "        print('Correct number of parameters in generator.')\n",
    "\n",
    "test_generator()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GAN Loss\n",
    "\n",
    "Compute the generator and discriminator loss. The generator loss is:\n",
    "$$\\ell_G  =  -\\mathbb{E}_{z \\sim p(z)}\\left[\\log D(G(z))\\right]$$\n",
    "and the discriminator loss is:\n",
    "$$ \\ell_D = -\\mathbb{E}_{x \\sim p_\\text{data}}\\left[\\log D(x)\\right] - \\mathbb{E}_{z \\sim p(z)}\\left[\\log \\left(1-D(G(z))\\right)\\right]$$\n",
    "Note that these are negated from the equations presented earlier as we will be *minimizing* these losses.\n",
    "\n",
    "**HINTS**: You should use the `bce_loss` function defined below to compute the binary cross entropy loss which is needed to compute the log probability of the true label given the logits output from the discriminator. Given a score $s\\in\\mathbb{R}$ and a label $y\\in\\{0, 1\\}$, the binary cross entropy loss is\n",
    "\n",
    "$$ bce(s, y) = -y * \\log(s) - (1 - y) * \\log(1 - s) $$\n",
    "\n",
    "A naive implementation of this formula can be numerically unstable, so we have provided a numerically stable implementation for you below.\n",
    "\n",
    "You will also need to compute labels corresponding to real or fake and use the logit arguments to determine their size. Make sure you cast these labels to the correct data type using the global `dtype` variable, for example:\n",
    "\n",
    "\n",
    "`true_labels = torch.ones(size).type(dtype)`\n",
    "\n",
    "Instead of computing the expectation of $\\log D(G(z))$, $\\log D(x)$ and $\\log \\left(1-D(G(z))\\right)$, we will be averaging over elements of the minibatch, so make sure to combine the loss by averaging instead of summing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [],
   "source": [
    "def bce_loss(input, target):\n",
    "    \"\"\"\n",
    "    Numerically stable version of the binary cross-entropy loss function.\n",
    "\n",
    "    As per https://github.com/pytorch/pytorch/issues/751\n",
    "    See the TensorFlow docs for a derivation of this formula:\n",
    "    https://www.tensorflow.org/api_docs/python/tf/nn/sigmoid_cross_entropy_with_logits\n",
    "\n",
    "    Inputs:\n",
    "    - input: PyTorch Tensor of shape (N, ) giving scores.\n",
    "    - target: PyTorch Tensor of shape (N,) containing 0 and 1 giving targets.\n",
    "\n",
    "    Returns:\n",
    "    - A PyTorch Tensor containing the mean BCE loss over the minibatch of input data.\n",
    "    \"\"\"\n",
    "    neg_abs = - input.abs()\n",
    "    loss = input.clamp(min=0) - input * target + (1 + neg_abs.exp()).log()\n",
    "    return loss.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def discriminator_loss(logits_real, logits_fake):\n",
    "    \"\"\"\n",
    "    Computes the discriminator loss described above.\n",
    "    \n",
    "    Inputs:\n",
    "    - logits_real: PyTorch Tensor of shape (N,) giving scores for the real data.\n",
    "    - logits_fake: PyTorch Tensor of shape (N,) giving scores for the fake data.\n",
    "    \n",
    "    Returns:\n",
    "    - loss: PyTorch Tensor containing (scalar) the loss for the discriminator.\n",
    "    \"\"\"\n",
    "    loss = bce_loss(logits_real, torch.ones(logits_real.size()).type(dtype))+bce_loss(logits_fake, torch.zeros(logits_fake.size()).type(dtype))\n",
    "    return loss\n",
    "\n",
    "def generator_loss(logits_fake):\n",
    "    \"\"\"\n",
    "    Computes the generator loss described above.\n",
    "\n",
    "    Inputs:\n",
    "    - logits_fake: PyTorch Tensor of shape (N,) giving scores for the fake data.\n",
    "    \n",
    "    Returns:\n",
    "    - loss: PyTorch Tensor containing the (scalar) loss for the generator.\n",
    "    \"\"\"\n",
    "    loss = bce_loss(logits_fake, torch.ones(logits_fake.size()).type(dtype))\n",
    "    return loss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test your generator and discriminator loss. You should see errors < 1e-7."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum error in d_loss: 3.97058e-09\n"
     ]
    }
   ],
   "source": [
    "def test_discriminator_loss(logits_real, logits_fake, d_loss_true):\n",
    "    d_loss = discriminator_loss(torch.Tensor(logits_real).type(dtype),\n",
    "                                torch.Tensor(logits_fake).type(dtype)).cpu().numpy()\n",
    "    print(\"Maximum error in d_loss: %g\"%rel_error(d_loss_true, d_loss))\n",
    "\n",
    "test_discriminator_loss(answers['logits_real'], answers['logits_fake'],\n",
    "                        answers['d_loss_true'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum error in g_loss: 4.4518e-09\n"
     ]
    }
   ],
   "source": [
    "def test_generator_loss(logits_fake, g_loss_true):\n",
    "    g_loss = generator_loss(torch.Tensor(logits_fake).type(dtype)).cpu().numpy()\n",
    "    print(\"Maximum error in g_loss: %g\"%rel_error(g_loss_true, g_loss))\n",
    "\n",
    "test_generator_loss(answers['logits_fake'], answers['g_loss_true'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Optimizing our loss\n",
    "Make a function that returns an `optim.Adam` optimizer for the given model with a 1e-3 learning rate, beta1=0.5, beta2=0.999. You'll use this to construct optimizers for the generators and discriminators for the rest of the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_optimizer(model):\n",
    "    \"\"\"\n",
    "    Construct and return an Adam optimizer for the model with learning rate 1e-3,\n",
    "    beta1=0.5, and beta2=0.999.\n",
    "    \n",
    "    Input:\n",
    "    - model: A PyTorch model that we want to optimize.\n",
    "    \n",
    "    Returns:\n",
    "    - An Adam optimizer for the model with the desired hyperparameters.\n",
    "    \"\"\"\n",
    "    optimizer = optim.Adam(model.parameters(), lr = 1e-3, betas = (0.5, 0.999))\n",
    "    return optimizer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training a GAN!\n",
    "\n",
    "We provide you the main training loop... you won't need to change this function, but we encourage you to read through and understand it. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [],
   "source": [
    "def run_a_gan(D, G, D_solver, G_solver, discriminator_loss, generator_loss, show_every=250, \n",
    "              batch_size=128, noise_size=96, num_epochs=10):\n",
    "    \"\"\"\n",
    "    Train a GAN!\n",
    "    \n",
    "    Inputs:\n",
    "    - D, G: PyTorch models for the discriminator and generator\n",
    "    - D_solver, G_solver: torch.optim Optimizers to use for training the\n",
    "      discriminator and generator.\n",
    "    - discriminator_loss, generator_loss: Functions to use for computing the generator and\n",
    "      discriminator loss, respectively.\n",
    "    - show_every: Show samples after every show_every iterations.\n",
    "    - batch_size: Batch size to use for training.\n",
    "    - noise_size: Dimension of the noise to use as input to the generator.\n",
    "    - num_epochs: Number of epochs over the training dataset to use for training.\n",
    "    \"\"\"\n",
    "    iter_count = 0\n",
    "    for epoch in range(num_epochs):\n",
    "        for x, _ in loader_train:\n",
    "            if len(x) != batch_size:\n",
    "                continue\n",
    "            D_solver.zero_grad()\n",
    "            real_data = x.type(dtype)\n",
    "            logits_real = D(2* (real_data - 0.5)).type(dtype)\n",
    "\n",
    "            g_fake_seed = sample_noise(batch_size, noise_size).type(dtype)\n",
    "            fake_images = G(g_fake_seed).detach()\n",
    "            logits_fake = D(fake_images.view(batch_size, 1, 28, 28))\n",
    "\n",
    "            d_total_error = discriminator_loss(logits_real, logits_fake)\n",
    "            d_total_error.backward()        \n",
    "            D_solver.step()\n",
    "\n",
    "            G_solver.zero_grad()\n",
    "            g_fake_seed = sample_noise(batch_size, noise_size).type(dtype)\n",
    "            fake_images = G(g_fake_seed)\n",
    "\n",
    "            gen_logits_fake = D(fake_images.view(batch_size, 1, 28, 28))\n",
    "            g_error = generator_loss(gen_logits_fake)\n",
    "            g_error.backward()\n",
    "            G_solver.step()\n",
    "\n",
    "            if (iter_count % show_every == 0):\n",
    "                print('Iter: {}, D: {:.4}, G:{:.4}'.format(iter_count,d_total_error.item(),g_error.item()))\n",
    "                imgs_numpy = fake_images.data.cpu().numpy()\n",
    "                show_images(imgs_numpy[0:16])\n",
    "                plt.show()\n",
    "                print()\n",
    "            iter_count += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter: 0, D: 1.38, G:0.7021\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 250, D: 1.316, G:1.089\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 500, D: 1.202, G:1.234\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 750, D: 1.116, G:1.522\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1000, D: 1.203, G:0.9437\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1250, D: 1.167, G:1.078\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1500, D: 1.173, G:0.8004\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1750, D: 1.258, G:1.037\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 2000, D: 1.292, G:1.066\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 2250, D: 1.387, G:0.9539\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 2500, D: 1.387, G:0.8981\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 2750, D: 1.325, G:0.799\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 3000, D: 1.322, G:0.7518\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 3250, D: 1.269, G:0.8522\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 3500, D: 1.349, G:0.7761\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 3750, D: 1.352, G:0.7272\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# Make the discriminator\n",
    "D = discriminator().type(dtype)\n",
    "\n",
    "# Make the generator\n",
    "G = generator().type(dtype)\n",
    "\n",
    "# Use the function you wrote earlier to get optimizers for the Discriminator and the Generator\n",
    "D_solver = get_optimizer(D)\n",
    "G_solver = get_optimizer(G)\n",
    "# Run it!\n",
    "run_a_gan(D, G, D_solver, G_solver, discriminator_loss, generator_loss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "source": [
    "Well that wasn't so hard, was it? In the iterations in the low 100s you should see black backgrounds, fuzzy shapes as you approach iteration 1000, and decent shapes, about half of which will be sharp and clearly recognizable as we pass 3000."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Least Squares GAN\n",
    "We'll now look at [Least Squares GAN](https://arxiv.org/abs/1611.04076), a newer, more stable alernative to the original GAN loss function. For this part, all we have to do is change the loss function and retrain the model. We'll implement equation (9) in the paper, with the generator loss:\n",
    "$$\\ell_G  =  \\frac{1}{2}\\mathbb{E}_{z \\sim p(z)}\\left[\\left(D(G(z))-1\\right)^2\\right]$$\n",
    "and the discriminator loss:\n",
    "$$ \\ell_D = \\frac{1}{2}\\mathbb{E}_{x \\sim p_\\text{data}}\\left[\\left(D(x)-1\\right)^2\\right] + \\frac{1}{2}\\mathbb{E}_{z \\sim p(z)}\\left[ \\left(D(G(z))\\right)^2\\right]$$\n",
    "\n",
    "\n",
    "**HINTS**: Instead of computing the expectation, we will be averaging over elements of the minibatch, so make sure to combine the loss by averaging instead of summing. When plugging in for $D(x)$ and $D(G(z))$ use the direct output from the discriminator (`scores_real` and `scores_fake`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ls_discriminator_loss(scores_real, scores_fake):\n",
    "    \"\"\"\n",
    "    Compute the Least-Squares GAN loss for the discriminator.\n",
    "    \n",
    "    Inputs:\n",
    "    - scores_real: PyTorch Tensor of shape (N,) giving scores for the real data.\n",
    "    - scores_fake: PyTorch Tensor of shape (N,) giving scores for the fake data.\n",
    "    \n",
    "    Outputs:\n",
    "    - loss: A PyTorch Tensor containing the loss.\n",
    "    \"\"\"\n",
    "    loss = None\n",
    "    # *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "    loss = (scores_real - 1).pow(2).mean() + (scores_fake).pow(2).mean()\n",
    "    loss /= 2\n",
    "\n",
    "    # *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "    return loss\n",
    "\n",
    "def ls_generator_loss(scores_fake):\n",
    "    \"\"\"\n",
    "    Computes the Least-Squares GAN loss for the generator.\n",
    "    \n",
    "    Inputs:\n",
    "    - scores_fake: PyTorch Tensor of shape (N,) giving scores for the fake data.\n",
    "    \n",
    "    Outputs:\n",
    "    - loss: A PyTorch Tensor containing the loss.\n",
    "    \"\"\"\n",
    "    loss = (scores_fake - 1).pow(2).mean()/2\n",
    "    return loss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before running a GAN with our new loss function, let's check it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum error in d_loss: 1.53171e-08\n",
      "Maximum error in g_loss: 2.7837e-09\n"
     ]
    }
   ],
   "source": [
    "def test_lsgan_loss(score_real, score_fake, d_loss_true, g_loss_true):\n",
    "    score_real = torch.Tensor(score_real).type(dtype)\n",
    "    score_fake = torch.Tensor(score_fake).type(dtype)\n",
    "    d_loss = ls_discriminator_loss(score_real, score_fake).cpu().numpy()\n",
    "    g_loss = ls_generator_loss(score_fake).cpu().numpy()\n",
    "    print(\"Maximum error in d_loss: %g\"%rel_error(d_loss_true, d_loss))\n",
    "    print(\"Maximum error in g_loss: %g\"%rel_error(g_loss_true, g_loss))\n",
    "\n",
    "test_lsgan_loss(answers['logits_real'], answers['logits_fake'],\n",
    "                answers['d_loss_lsgan_true'], answers['g_loss_lsgan_true'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the following cell to train your model!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter: 0, D: 0.4856, G:0.4893\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 250, D: 0.1, G:0.2631\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 500, D: 0.225, G:0.6342\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 750, D: 0.1186, G:0.2954\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1000, D: 0.1589, G:0.1993\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1250, D: 0.09808, G:0.4577\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1500, D: 0.1549, G:0.3103\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1750, D: 0.1628, G:0.3099\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 2000, D: 0.1707, G:0.3086\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 2250, D: 0.2082, G:0.2151\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 2500, D: 0.2557, G:0.1566\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 2750, D: 0.2308, G:0.1775\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 3000, D: 0.2455, G:0.1689\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 3250, D: 0.2205, G:0.1549\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 3500, D: 0.2506, G:0.1726\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 3750, D: 0.2247, G:0.1383\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "D_LS = discriminator().type(dtype)\n",
    "G_LS = generator().type(dtype)\n",
    "\n",
    "D_LS_solver = get_optimizer(D_LS)\n",
    "G_LS_solver = get_optimizer(G_LS)\n",
    "\n",
    "run_a_gan(D_LS, G_LS, D_LS_solver, G_LS_solver, ls_discriminator_loss, ls_generator_loss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Deeply Convolutional GANs\n",
    "In the first part of the notebook, we implemented an almost direct copy of the original GAN network from Ian Goodfellow. However, this network architecture allows no real spatial reasoning. It is unable to reason about things like \"sharp edges\" in general because it lacks any convolutional layers. Thus, in this section, we will implement some of the ideas from [DCGAN](https://arxiv.org/abs/1511.06434), where we use convolutional networks \n",
    "\n",
    "#### Discriminator\n",
    "We will use a discriminator inspired by the TensorFlow MNIST classification tutorial, which is able to get above 99% accuracy on the MNIST dataset fairly quickly. \n",
    "* Reshape into image tensor (Use Unflatten!)\n",
    "* Conv2D: 32 Filters, 5x5, Stride 1\n",
    "* Leaky ReLU(alpha=0.01)\n",
    "* Max Pool 2x2, Stride 2\n",
    "* Conv2D: 64 Filters, 5x5, Stride 1\n",
    "* Leaky ReLU(alpha=0.01)\n",
    "* Max Pool 2x2, Stride 2\n",
    "* Flatten\n",
    "* Fully Connected with output size 4 x 4 x 64\n",
    "* Leaky ReLU(alpha=0.01)\n",
    "* Fully Connected with output size 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([128, 1])\n"
     ]
    }
   ],
   "source": [
    "def build_dc_classifier():\n",
    "    \"\"\"\n",
    "    Build and return a PyTorch model for the DCGAN discriminator implementing\n",
    "    the architecture above.\n",
    "    \"\"\"\n",
    "    return nn.Sequential(\n",
    "        # *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "        nn.Conv2d(1, 32, 5, stride = 1),\n",
    "        nn.LeakyReLU(0.01),\n",
    "        nn.MaxPool2d(2, 2),\n",
    "        nn.Conv2d(32, 64, 5, stride = 1),\n",
    "        nn.LeakyReLU(0.01),\n",
    "        nn.MaxPool2d(2, 2),\n",
    "        Flatten(),\n",
    "        nn.Linear(4*4*64, 4*4*64),\n",
    "        nn.LeakyReLU(0.01),\n",
    "        nn.Linear(4*4*64, 1),\n",
    "\n",
    "        # *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "    )\n",
    "\n",
    "data = next(enumerate(loader_train))[-1][0].type(dtype)\n",
    "b = build_dc_classifier().type(dtype)\n",
    "out = b(data)\n",
    "print(out.size())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the number of parameters in your classifier as a sanity check:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct number of parameters in generator.\n"
     ]
    }
   ],
   "source": [
    "def test_dc_classifer(true_count=1102721):\n",
    "    model = build_dc_classifier()\n",
    "    cur_count = count_params(model)\n",
    "    if cur_count != true_count:\n",
    "        print('Incorrect number of parameters in generator. Check your achitecture.')\n",
    "    else:\n",
    "        print('Correct number of parameters in generator.')\n",
    "\n",
    "test_dc_classifer()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Generator\n",
    "For the generator, we will copy the architecture exactly from the [InfoGAN paper](https://arxiv.org/pdf/1606.03657.pdf). See Appendix C.1 MNIST. See the documentation for [tf.nn.conv2d_transpose](https://www.tensorflow.org/api_docs/python/tf/nn/conv2d_transpose). We are always \"training\" in GAN mode. \n",
    "* Fully connected with output size 1024\n",
    "* `ReLU`\n",
    "* BatchNorm\n",
    "* Fully connected with output size 7 x 7 x 128 \n",
    "* ReLU\n",
    "* BatchNorm\n",
    "* Reshape into Image Tensor of shape 7, 7, 128\n",
    "* Conv2D^T (Transpose): 64 filters of 4x4, stride 2, 'same' padding (use `padding=1`)\n",
    "* `ReLU`\n",
    "* BatchNorm\n",
    "* Conv2D^T (Transpose): 1 filter of 4x4, stride 2, 'same' padding (use `padding=1`)\n",
    "* `TanH`\n",
    "* Should have a 28x28x1 image, reshape back into 784 vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([128, 784])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def build_dc_generator(noise_dim=NOISE_DIM):\n",
    "    \"\"\"\n",
    "    Build and return a PyTorch model implementing the DCGAN generator using\n",
    "    the architecture described above.\n",
    "    \"\"\"\n",
    "    return nn.Sequential(\n",
    "        # *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "        nn.Linear(noise_dim, 1024),\n",
    "        nn.ReLU(),\n",
    "        nn.BatchNorm1d(1024),\n",
    "        nn.Linear(1024, 7*7*128),\n",
    "        nn.ReLU(),\n",
    "        nn.BatchNorm1d(7*7*128),\n",
    "        Unflatten(),\n",
    "        torch.nn.ConvTranspose2d(128, 64, 4, stride = 2, padding = 1),\n",
    "        nn.ReLU(),\n",
    "        nn.BatchNorm2d(64),\n",
    "        torch.nn.ConvTranspose2d(64, 1, 4, stride = 2, padding = 1),\n",
    "        nn.Tanh(),\n",
    "        Flatten(),\n",
    "\n",
    "        # *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "    )\n",
    "\n",
    "test_g_gan = build_dc_generator().type(dtype)\n",
    "test_g_gan.apply(initialize_weights)\n",
    "\n",
    "fake_seed = torch.randn(batch_size, NOISE_DIM).type(dtype)\n",
    "fake_images = test_g_gan.forward(fake_seed)\n",
    "fake_images.size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the number of parameters in your generator as a sanity check:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct number of parameters in generator.\n"
     ]
    }
   ],
   "source": [
    "def test_dc_generator(true_count=6580801):\n",
    "    model = build_dc_generator(4)\n",
    "    cur_count = count_params(model)\n",
    "    if cur_count != true_count:\n",
    "        print('Incorrect number of parameters in generator. Check your achitecture.')\n",
    "    else:\n",
    "        print('Correct number of parameters in generator.')\n",
    "\n",
    "test_dc_generator()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter: 0, D: 1.362, G:0.1309\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 250, D: 1.387, G:0.6395\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 500, D: 1.233, G:0.8587\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 750, D: 1.264, G:0.7925\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1000, D: 1.313, G:0.8431\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1250, D: 1.23, G:1.009\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1500, D: 1.206, G:0.7966\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Iter: 1750, D: 1.369, G:0.7725\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "D_DC = build_dc_classifier().type(dtype) \n",
    "D_DC.apply(initialize_weights)\n",
    "G_DC = build_dc_generator().type(dtype)\n",
    "G_DC.apply(initialize_weights)\n",
    "\n",
    "D_DC_solver = get_optimizer(D_DC)\n",
    "G_DC_solver = get_optimizer(G_DC)\n",
    "\n",
    "run_a_gan(D_DC, G_DC, D_DC_solver, G_DC_solver, discriminator_loss, generator_loss, num_epochs=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "## INLINE QUESTION 1\n",
    "\n",
    "We will look at an example to see why alternating minimization of the same objective (like in a GAN) can be tricky business.\n",
    "\n",
    "Consider $f(x,y)=xy$. What does $\\min_x\\max_y f(x,y)$ evaluate to? (Hint: minmax tries to minimize the maximum value achievable.)\n",
    "\n",
    "Now try to evaluate this function numerically for 6 steps, starting at the point $(1,1)$, \n",
    "by using alternating gradient (first updating y, then updating x using that updated y) with step size $1$. **Here step size is the learning_rate, and steps will be learning_rate * gradient.**\n",
    "You'll find that writing out the update step in terms of $x_t,y_t,x_{t+1},y_{t+1}$ will be useful.\n",
    "\n",
    "Breifly explain what $\\min_x\\max_y f(x,y)$ evaluates to and record the six pairs of explicit values for $(x_t,y_t)$ in the table below.\n",
    "\n",
    "### Your answer:\n",
    "\n",
    " \n",
    " $y_0$ | $y_1$ | $y_2$ | $y_3$ | $y_4$ | $y_5$ | $y_6$ \n",
    " ----- | ----- | ----- | ----- | ----- | ----- | ----- \n",
    "   1   |   2   |   1   |  -1   |   -2  |   -1  |   1   \n",
    " $x_0$ | $x_1$ | $x_2$ | $x_3$ | $x_4$ | $x_5$ | $x_6$ \n",
    "   1   |   -1  |  -2   |  -1   |   1   |   2   |   1   \n",
    "   \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "## INLINE QUESTION 2\n",
    "Using this method, will we ever reach the optimal value? Why or why not?\n",
    "\n",
    "### Your answer: \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "## INLINE QUESTION 3\n",
    "If the generator loss decreases during training while the discriminator loss stays at a constant high value from the start, is this a good sign? Why or why not? A qualitative answer is sufficient.\n",
    "\n",
    "### Your answer: \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "tags": [
     "pdf-inline"
    ]
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
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 },
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